Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Streaming Multi-Context Systems
Authors: Minh Dao-Tran, Thomas Eiter
IJCAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We thus present streaming MCS, which have a run-based semantics that accounts for asynchronous, distributed execution and supports obtaining equilibria for contexts in cyclic exchange (avoiding infinite loops); moreover, they equip MCS with native stream reasoning features. Ad-hoc query answering is NP-complete while prediction is PSpace-complete in relevant settings (but undecidable in general); tractability results for suitable restrictions. |
| Researcher Affiliation | Academia | Minh Dao-Tran and Thomas Eiter Institute of Information Systems, Vienna University of Technology Favoritenstraße 9-11, A-1040 Vienna, Austria EMAIL |
| Pseudocode | No | The paper focuses on theoretical definitions, semantics, and complexity analysis. It does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide or link to any open-source code for the methodology it describes. It mentions in 'Future Work' the intention to '(iii) implement a prototype of s MCS based on the DMCS system [Dao Tran et al., 2015] for MCS evaluation'. |
| Open Datasets | No | The paper is theoretical and does not conduct experiments with datasets; thus, it does not mention training datasets or their availability. |
| Dataset Splits | No | The paper is theoretical and does not conduct experiments with datasets; thus, it does not mention validation splits. |
| Hardware Specification | No | The paper is theoretical and does not describe any empirical experiments or implementations that would require hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not describe an implementation; thus, it does not list any software dependencies with specific version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any empirical experiments; thus, it does not include details on experimental setup or hyperparameters. |